Perceptual quality metrics applied to still image compression

Eckert, Michael P.; Bradley, Andrew P.

doi:10.1016/s0165-1684(98)00124-8

Cited by 304 publications

(179 citation statements)

References 70 publications

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“…The comparisons are made at four logarithmically spaced bit-rates (and hence varying image qualities) of 0.125, 0.25, 0.5, and 1 bits per pixel (bpp). A two alternative forced choice (2AFC) methodology was selected because of its simplicity, i.e., the observer views the two images and then selects the one preferred, and so there are no issues with scaling opinion scores between different observers (Eckert and Bradley, 1998). There were ten observers (8 male and 2 female) all with good, or corrected, vision and all observers were non-experts in image compression.…”

Section: Experimental Methodologymentioning

confidence: 99%

Visual attention for region of interest coding in JPEG 2000

Bradley

Stentiford

2003

Journal of Visual Communication and Image Representation

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This paper details work undertaken on the application of an algorithm for visual attention (VA) to region of interest (ROI) coding in JPEG 2000 (JP2K). In this way, an ''interest ordered'' progressive bit-stream is produced where the regions highlighted by the VA algorithm are presented first in bit-stream. The paper briefly outlines the terminology used in JP2K, the packet structure of the bit-stream, and the methods available to achieve ROI coding in JP2K (tiling, coefficient scaling, and code-block selection). The paper then describes how the output of the VA algorithm is post-processed so that an ROI is produced that can be efficiently coded using coefficient scaling in JP2K. Finally, a two alternative forced choice (2AFC) visual trial is undertaken to compare the visual quality of images encoded using the proposed VA ROI algorithm and conventional JP2K. The experimental results show that, while there is no overall preference for the VA ROI encoded images; there is an improvement in perceived image quality at low bit rates (below 0.25 bits per pixel). It is concluded that an overall increase in image quality only occurs when the increase in quality of the ROI more than compensates for the decrease in quality of the image background (i.e., non-ROI).

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Section: Experimental Methodologymentioning

confidence: 99%

Visual attention for region of interest coding in JPEG 2000

Bradley

Stentiford

2003

Journal of Visual Communication and Image Representation

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“…Regardless of its significant drawbacks (mainly its low correlation with subjective estimations) [39][40][41][42][43], PSNR is still very present in video quality analysis. It is easy to compute and provides a first impression on the quality achieved.…”

Section: Psnrmentioning

confidence: 99%

Computational Inference and Control of Quality in Multimedia Services

Menkovski

2015

Springer Theses

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Please check the document version of this publication:• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:www.tue.nl/taverne Take down policyIf you believe that this document breaches copyright please contact us at:openaccess@tue.nl providing details and we will investigate your claim. Copyright c 2013 by Vlado Menkovski All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means without the prior written consent of the author. Typeset using L A T E X, printed in The NetherlandsTo my parents, Angel who dedicated his life to his sons and Snežana whose strength inspires me deeply. SummaryQuality is the degree of excellence we expect of a service or a product. It is also one of the key factors that determine its value. For multimedia services, understanding the experienced quality means understanding how the delivered fidelity, precision and reliability correspond to the users' expectations. Yet the quality of multimedia services is inextricably linked to the underlying technology. It is developments in video recording, compression and transport as well as display technologies that enables high quality multimedia services to become ubiquitous. The constant evolution of these technologies delivers a steady increase in performance, but also a growing level of complexity. As new technologies stack on top of each other the interactions between them and their components become more intricate and obscure. In this environment optimizing the delivered quality of multimedia services becomes increasingly challenging. The factors that affect the experienced quality, or Quality of Experience (QoE), tend to have complex non-linear relat...

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“…MSE basedencoder may allocate more bits to these visuallysaturated areas since there are still computable PSNR gains. [9][10][11][12] Analysis of various sequences for variation in block size is done using full search method. Table 1 compares the value of PSNR and the time required to complete the motion estimation.…”

Section: Adaptive Selection Of Motion Estimation Block Sizementioning

confidence: 99%

Adaptive Selection of Motion Estimation Block Size for Rate-Distortion Optimization

Gohokar¹,

Gohokar²

2011

IJCA

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The employment of the Variable Block size motion estimation technique introduces a new optimization issue for the motion compensated transform coding. An increase in bit rate allocation is necessary to accommodate VBS motion vectors. An algorithm for adaptive selection of motion estimation block size is proposed for R-D optimal motion estimation. It avoids reduction in the block size in visually irrelevant areas. Improvement in R-D performance is obtained at reduced complexity. General TermsVideo Compression

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Perceptual quality metrics applied to still image compression

Cited by 304 publications

References 70 publications

Visual attention for region of interest coding in JPEG 2000

Visual attention for region of interest coding in JPEG 2000

Computational Inference and Control of Quality in Multimedia Services

Adaptive Selection of Motion Estimation Block Size for Rate-Distortion Optimization

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